ORIGINAL RESEARCH
published: 01 March 2022
doi: 10.3389/fcvm.2022.823076
N-Terminal Pro-B-Type Natriuretic
Peptide in Risk Stratification of Heart
Failure Patients With Implantable
Cardioverter-Defibrillator
Yu Deng, Si-Jing Cheng, Wei Hua*, Min-Si Cai, Ni-Xiao Zhang, Hong-Xia Niu,
Xu-Hua Chen, Min Gu, Chi Cai, Xi Liu, Hao Huang and Shu Zhang
Cardiac Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical
Sciences and Peking Union Medical College, Beijing, China
Background: The prognostic value of N-terminal pro-B-type natriuretic peptide (NTproBNP) in heart failure (HF) is well-established. However, whether it could facilitate
the risk stratification of HF patients with implantable cardioverter-defibrillator (ICD) is
still unclear.
Edited by:
Julia W. Erath,
University Hospital Frankfurt, Germany
Reviewed by:
Emanuele Micaglio,
IRCCS San Donato Polyclinic, Italy
Ibrahim El-Battrawy,
Heidelberg University, Germany
*Correspondence:
Wei Hua
drhuaweifw@sina.com
Specialty section:
This article was submitted to
Cardiac Rhythmology,
a section of the journal
Frontiers in Cardiovascular Medicine
Received: 26 November 2021
Accepted: 01 February 2022
Published: 01 March 2022
Citation:
Deng Y, Cheng S-J, Hua W, Cai M-S,
Zhang N-X, Niu H-X, Chen X-H, Gu M,
Cai C, Liu X, Huang H and Zhang S
(2022) N-Terminal Pro-B-Type
Natriuretic Peptide in Risk Stratification
of Heart Failure Patients With
Implantable Cardioverter-Defibrillator.
Front. Cardiovasc. Med. 9:823076.
doi: 10.3389/fcvm.2022.823076
Objective: To determine the associations between baseline NT-proBNP and outcomes
of all-cause mortality and first appropriate shock due to sustained ventricular
tachycardia/ventricular fibrillation (VT/VF) in ICD recipients.
Methods and results: N-terminal pro-B-type natriuretic peptide was measured before
ICD implant in 500 patients (mean age 60.2 ± 12.0 years; 415 (83.0%) men; 231
(46.2%) Non-ischemic dilated cardiomyopathy (DCM); 136 (27.2%) primary prevention).
The median NT-proBNP was 854.3 pg/ml (interquartile range [IQR]: 402.0 to 1,817.8
pg/ml). We categorized NT-proBNP levels into quartiles and used a restricted cubic
spline to evaluate its nonlinear association with outcomes. The incidence rates of
mortality and first appropriate shock were 5.6 and 9.1%, respectively. After adjusting
for confounding factors, multivariable Cox regression showed a rise in NT-proBNP
was associated with an increased risk of all-cause mortality. Compared with the
lowest quartile, the hazard ratios (HRs) with 95% CI across increasing quartiles
were 1.77 (0.71, 4.43), 3.98 (1.71, 9.25), and 5.90 (2.43, 14.30) for NT-proBNP
(p for trend < 0.001). A restricted cubic spline demonstrated a similar pattern
with an inflection point found at 3,231.4 pg/ml, beyond which the increase in NTproBNP was not associated with increased mortality (p for nonlinearity < 0.001).
Fine-Gray regression was used to evaluate the association between NT-proBNP
and first appropriate shock accounting for the competing risk of death. In the
unadjusted, partial, and fully adjusted analysis, however, no significant association
could be found regardless of NT-proBNP as a categorical variable or log-transformed
continuous variable (all p > 0.05). No nonlinearity was found, either (p = 0.666).
Interactions between NT-proBNP and predefined factors were not found (all p > 0.1).
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NT-proBNP in Implantable Cardioverter-Defibrillator
Conclusion: In HF patients with ICD, the rise in NT-proBNP is independently associated
with increased mortality until it reaches the inflection point. However, its association with
the first appropriate shock was not found. Patients with higher NT-proBNP levels might
derive less benefit from ICD implant.
Keywords: N-terminal pro-B-type natriuretic peptide, heart failure, implantable cardioverter-defibrillator, all-cause
mortality, appropriate defibrillator shock, restricted cubic spline
INTRODUCTION
1, 2020 were enrolled. Ischemic cardiomyopathy (ICM) was
defined as left ventricular systolic dysfunction with marked
coronary stenosis (28). Non-ischemic DCM was defined as
ventricular dilatation and systolic dysfunction in the absence
of abnormal loading conditions and marked stenosis (29). The
exclusion criteria were (1) age <18 years (n = 2), (2) had
previous pacemaker or ICD (n = 38), (3) did not fulfill at least
one interrogation follow-up (n = 67), (4) failed to fulfill the
current guideline indication for implantation (6, 7) (n = 25),
(5) had missing NT-proBNP (n = 35), and (6) hospitalized
for acute HF within a week (n = 22). Figure 1 shows the
flowchart of the selection of the study population. The study
complied with the Declaration of Helsinki and was approved
by the Ethics Committee of Fuwai Hospital. All patients gave
informed consent.
Sudden cardiac death (SCD) represents a heavy health burden
accounting for 15–20% of all deaths around the world (1, 2).
Although advances in resuscitation and defibrillation have been
made throughout these years, more than 80% of individuals
experiencing SCD still could not survive hospital discharge (3, 4).
Most SCD events occur in the community-based population
without a prior history of structural heart disease, making it
difficult to predict (5). Therefore, preventive strategies have
been focusing on the high-risk population, such as those with
severe heart disease. An implantable cardioverter-defibrillator
(ICD) therapy is the widely accepted effective modality to reduce
SCD in current guidelines (6, 7). Nevertheless, the selection of
patients is mainly based on New York Heart Association (NYHA)
functional class and left ventricular ejection fraction (LVEF)
(6, 7). A large number of ICD recipients, especially those with
Non-ischemic etiology, do not receive appropriate therapy in the
long-term follow-up (8–14). Therefore, there is an urgent need
to find an additional indicator to identify patients more likely to
benefit from ICD therapy.
N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a
hormone secreted primarily by the ventricular myocardium in
response to increased wall stress due to volume expansion and/or
pressure overload in heart failure (HF) patients (15). It is an
established biomarker of HF diagnosis and prognosis (15, 16).
Moreover, it is recognized as a surrogate indicator for all-cause
mortality, HF hospitalization, and HF death (16). In addition,
it is associated with myocardial fibrosis (17), which is a wellestablished arrhythmogenic substrate (18–20). Prior studies have
proven that it is associated with an increased risk of SCD both
in the general population and patients with heart disease (21–
27). This makes it a promising biomarker for risk stratification
in patients with ICD. However, because it might increase the
occurrence of both SCD and pump failure death, it must be
systematically evaluated before it can be applied in the decisionmaking process of ICD implantation.
The purpose of the present study was to explore the role of
NT-proBNP in the risk stratification of HF patients with ICD. To
address this hypothesis, we tested its relationship with outcomes
of all-cause mortality and first appropriate shock in a population
of ischemic or Non-ischemic dilated cardiomyopathy (DCM).
Data Collection and Device Programming
Information about demographic characteristics, physical
examination, comorbidities, NYHA functional class, and
medication history was collected from electronic medical
records, which were obtained by trained clinicians at admission.
ECGs were obtained by experienced physicians. Blood samples
from the participants were taken in the fasting state. NT-proBNP
levels were measured within 3 days before ICD implant, using
an electrochemiluminescence immunoassay (Roche, Basel,
Switzerland) with a limit of quantification (LoQ) of 50 pg/ml by
experienced operators.
Although devices were programmed at the discretion of
treating physicians, shocks were delivered in the ventricular
tachycardia/ventricular fibrillation (VT/VF) zone if the
arrhythmia was not terminated by anti-tachycardia pacing
or initially applied in the VF zone. Device interrogation
results were adjudicated by experienced electrophysiologists.
Appropriate therapies were defined as therapies delivered
for VT/VF.
Outcomes
The primary endpoint was all-cause mortality. The survival
status was confirmed with medical death records or telephone
calls to the patients’ relatives or themselves until June 2021.
The secondary endpoint was the first appropriate ICD shock.
Patients were required to complete device interrogation every 6–
12 months or unintended visits after sensing therapies by ICD
until June 2021. The dates for the censoring of survival status
and interrogation information were not necessarily the same. The
appropriate shock was the only type of ICD therapy selected for
Study Patients
In total, 689 consecutive patients with ischemic or Non-ischemic
dilated cardiomyopathy disease implanted with ICD (single
or dual chamber) between January 1, 2013 and September
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NT-proBNP in Implantable Cardioverter-Defibrillator
FIGURE 1 | Flowchart on patient inclusion and exclusion.
the secondary endpoint because it was set only to treat the rapid
sustained VT or VF (28).
outcomes of all-cause mortality and first appropriate shock
after adjusting for confounding factors significant in univariable
analyses. Nonlinearity was tested by the Wald statistics. If this
was detected, we calculated the inflection point by a recursive
algorithm to calculate the places where the second derivative of
the fitted spline equaled to zero.
Several interactions between NT-proBNP quartiles and
baseline characteristics were considered. These included age,
gender, body mass index (BMI), primary/secondary prevention
indication, ICM/DCM, NYHA functional class, presence of
atrial fibrillation (AF), creatinine, and LVEF (≤35% or >35%).
Interactions between variables were considered significant at the
value of p ≤ 0.1.
Additional sensitivity analyses to evaluate the robustness of
our results were also conducted. (1) We replaced LVEF with
LVEDD in the multivariable model. (2) We further adjusted for
all covariates presented in Table 1 using stepwise selection by
AIC rule with the forced entry of NT-proBNP quartiles.
All analyses were performed using Stata 16.1/IC (StataCorp,
College Station, TX) and R 4.1.1 (R Core Development Team,
Vienna, Austria), such as the “rm,” “mstat,” “cmprs,” and
“survival” packages. A two-sided p ≤ 0.05 was considered
statistically significant if not otherwise specified.
Statistics
Continuous data are expressed as mean ± SD or the median
with the interquartile range (IQR) as appropriate; categorical
data are presented as frequencies and percentages. Patients were
divided into four groups according to baseline NT-proBNP
quartiles. In addition, NT-proBNP was log10 -transformed for
its skewed distribution. Baseline characteristics of the groups
were compared with one-way ANOVA for normally distributed
continuous variables, the Kruskal–Wallis test for Non-normally
distributed continuous variables, and the χ 2 test for categorical
variables. Univariable predictors significant at the p < 0.10
level were entered into the subsequent multivariable model.
Kaplan–Meier curves were constructed for all-cause mortality,
and cumulative incidence curves were constructed for the
first appropriate shock. The log-rank test and Fine–Gray
test were used to investigate the unadjusted differences of
primary and secondary endpoints between groups, respectively.
Multivariable Cox proportional hazards models were used to
assess the association between NT-proBNP quartiles and allcause mortality. A Fine–Gray subdistribution hazard model
accounting for the competing risk of death was used to
assess the association between NT-proBNP quartiles and first
appropriate shock. To eliminate the collinearity between LVEF
and left ventricular end-diastolic dimension (LVEDD), only
LVEF was kept in the multivariable model. The proportionalhazard assumption was assessed with Schoenfeld residuals, and
no violations were found. The lowest NT-proBNP quartile was
served as the reference group. Tests for trends were calculated
by including each corresponding quartile as a continuous
numeric variable in the models. Event rates were reported
per 100 person-years.
Furthermore, we used a restricted cubic spline with 3 knots
according to the Akaike information criterion (AIC) to flexibly
model the potential nonlinear effects of NT-proBNP with the
Frontiers in Cardiovascular Medicine | www.frontiersin.org
RESULTS
Finally, a total of 500 patients were included. The baseline
characteristics of patients according to the NT-proBNP
quartiles are presented in Table 1. The study population was
predominantly male (83.0%). The mean age was 60.2 ± 12.0
years. Median NT-proBNP was 854.3 pg/ml (IQR: 402.0 to
1,817.8 pg/ml). Patients with higher NT-proBNP were more
likely to be older, Non-smokers, and have more prevalent DCM,
diabetes, and AF (all p < 0.05). These patients were more likely
to have lower BMI, higher NYHA functional class, lower LVEF,
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TABLE 1 | Clinical characteristics of all patients in terms of baseline NT-proBNP quartiles.
Characteristics
All Patients
(n = 500)
Quartile 1
(n = 125)
Quartile 2
(n = 125)
Quartile 3
(n = 125)
Quartile 4
(n = 125)
P-value
NT-proBNP
(pg/mL)
854.2 [402.0;
1,817.8]
219.2 [122.7;
299.5]
625.3 [515.4;
717.3]
1,198.0 [1,029.7;
1,467.0]
3,121.0 [2,296.0;
4,609.7]
<0.001
log-transformed
NT-proBNP
2.92 ± 0.49
2.27 ± 0.28
2.78 ± 0.09
3.09 ± 0.10
3.53 ± 0.19
<0.001
Age (years)
60.2 ± 12.0
57.6 ± 12.5
59.3 ± 11.5
60.7 ± 11.9
63.1 ± 11.7
0.003
Male sex
415 (83.0%)
111 (88.8%)
105 (84.0%)
101 (80.8%)
98 (78.4%)
0.146
Non-ischemic
etiology
231 (46.2%)
44 (35.2%)
58 (46.4%)
60 (48.0%)
69 (55.2%)
0.016
BMI (kg/m2 )
25.1 ± 3.5
25.7 ± 3.1
25.9 ± 3.5
24.9 ± 3.4
24.0 ± 3.7
<0.001
Current smoking
263 (52.6%)
74 (59.2%)
72 (57.6%)
63 (50.4%)
54 (43.2%)
0.044
Secondary
prevention
364 (72.8%)
97 (77.6%)
97 (77.6%)
89 (71.2%)
81 (64.8%)
0.068
0.143
Frequent PVCs
234 (46.8%)
55 (44.0%)
50 (40.0%)
62 (49.6%)
67 (53.6%)
NSVT
147 (29.4%)
42 (33.6%)
28 (22.4%)
34 (27.2%)
43 (34.4%)
0.121
Dual-chamber ICD
182 (36.4%)
38 (30.4%)
50 (40.0%)
48 (38.4%)
46 (36.8%)
0.412
I/II
295 (59.0%)
95 (76.0%)
85 (68.0%)
69 (55.2%)
46 (36.8%)
<0.001
III/IV
205 (41.0%)
30 (24.0%)
40 (32.0%)
56 (44.8%)
79 (63.2%)
<0.001
NYHA class
Echocardiogram
LVEDD (mm)
64.1 ± 9.25
61.1 ± 8.59
63.2 ± 9.29
65.0 ± 8.74
67.0 ± 9.40
<0.001
LVEF (%)
37.4 ± 11.1
42.8 ± 12.0
40.1 ± 11.8
35.3 ± 8.14
31.3 ± 8.12
<0.001
<0.001
Comorbidities
AF
136 (27.2%)
19 (15.2%)
26 (20.8%)
37 (29.6%)
54 (43.2%)
Hypertension
232 (46.4%)
56 (44.8%)
57 (45.6%)
56 (44.8%)
63 (50.4%)
0.779
Diabetes
120 (24.0%)
27 (21.6%)
24 (19.2%)
27 (21.6%)
42 (33.6%)
0.034
Laboratory tests
Hemoglobin (g/L)
143 ± 18.6
144 ± 14.2
145 ± 15.7
144 ± 21.2
138 ± 21.4
0.008
Creatinine
(µmol/L)
97.5 ± 27.8
89.0 ± 21.0
95.4 ± 23.7
95.6 ± 30.9
110 ± 30.1
<0.001
BUN (mmol/L)
7.50 ± 2.95
6.52 ± 2.39
7.19 ± 2.48
7.46 ± 3.19
8.82 ± 3.20
<0.001
Sodium (mmol/L)
140.0 ± 2.5
140.4 ± 2.0
140.0 ± 2.3
139.7 ± 2.7
140.0 ± 2.8
0.168
0.519
Medications
ACEI/ARB
383 (76.6%)
95 (76.0%)
101 (80.8%)
91 (72.8%)
96 (76.8%)
Sacubitril/valsartan
33 (6.60%)
12 (9.60%)
9 (7.20%)
6 (4.80%)
6 (4.80%)
0.360
Beta-blockers
428 (85.6%)
114 (91.2%)
105 (84.0%)
105 (84.0%)
104 (83.2%)
0.232
Amiodarone
297 (59.4%)
68 (54.4%)
76 (60.8%)
81 (64.8%)
72 (57.6%)
0.380
Diuretics
383 (76.6%)
77 (61.6%)
94 (75.2%)
104 (83.2%)
108 (86.4%)
<0.001
MRA
364 (72.8%)
92 (73.6%)
90 (72.0%)
90 (72.0%)
92 (73.6%)
0.984
Digitalis
107 (21.4%)
19 (15.2%)
23 (18.4%)
27 (21.6%)
38 (30.4%)
0.023
Statin
296 (59.2%)
82 (65.6%)
71 (56.8%)
74 (59.2%)
69 (55.2%)
0.355
Quartile 1: NT-proBNP ≤ 401.9 pg/ml, Quartile 2: 402.0 ≤ 854.2 pg/ml, Quartile 3: 854.3 ≤ 1,817.7 pg/mL, Quartile 4: ≥ 1,817.8 pg/ml.
Values are presented as mean ± SD, median, and interquartile range (IQR), or frequency (%).
ACEI/ARB, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker; AF, atrial fibrillation; BMI, body mass index; BUN, blood urea nitrogen; ICD, implantable cardioverterdefibrillator; LVEDD, left ventricular end-diastolic diameter; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonists; NYHA, New York Heart Association;
NT-proBNP, N-terminal pro-brain natriuretic peptide; NSVT, Non-sustained ventricular tachycardia; PVC, premature ventricular contractions.
Relationship Between NT-proBNP and
All-Cause Mortality
larger LVEDD, higher blood urea nitrogen and creatinine, and
receive diuretics and digoxin treatment at baseline (all p < 0.05).
Over a median survival follow-up of 4.1 (IQR 2.8–5.7) years,
106 patients died (incidence 5.61 per 100 person-years; 95%
CI 4.59–6.78 per 100 person-years). The median interrogation
follow-up was 1.7 (IQR 0.8–3.5) years, and 89 patients had their
first appropriate shock due to the sustained VT/VF (incidence
9.09 per 100 person-years; 95% CI 7.30–11.19 per 100 personyears). The incidence rates of the two outcomes according to
NT-proBNP quartiles are shown in Figure 2.
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Survival curves according to NT-proBNP quartiles are shown
in Figure 3A. Patients in the 1st and 2nd quartiles had similar
survival (p = 0.211), whereas patients in the 3rd and 4th
quartiles had significantly worse survival than those in the 1st
quartile (HR = 4.52, 95% CI: 1.99–10.25, P < 0.001; HR = 8.37,
95% CI: 3.80–18.42, p < 0.001, respectively). After adjusting
for confounding factors, such as age, smoking, prevention
indication, ICD/DCM, NYHA functional class, BMI, diabetes,
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NT-proBNP in Implantable Cardioverter-Defibrillator
FIGURE 2 | Outcomes in heart failure (HF) with implantable cardioverter-defibrillator (ICD) according to N-terminal pro-brain natriuretic peptide (NT–proBNP) quartiles.
significant in univariable analyses (all p > 0.05). Even after
further adjusting for other variables using the AIC rule, it was not
significant (p > 0.05). Additionally, we examined the potential
nonlinear association between NT-proBNP and first appropriate
shock using the restricted cubic spline, while no such association
was found (p for nonlinearity = 0.666). The interactions between
NT-proBNP and predefined factors were also not significant
(all p > 0.1). Sensitivity analyses by adjusting LVEDD showed
similar results. Instead, LVEDD itself was found to be a significant
predictor (per 5 mm increase, subdistribution HR = 1.13, 95% CI:
1.01–1.26, P = 0.035). Overall, we did not observe the association
between NT-proBNP levels and the first appropriate shock.
AF, hemoglobin, creatinine, LVEF, and the use of diuretics and
digoxin, compared with that in the lowest quartile, the hazard
ratios (HRs) with 95% CI across increasing quartiles were 1.77
(0.71, 4.43), 3.98 (1.71, 9.25), and 5.90 (2.43, 14.30) for NTproBNP, as shown in Table 2. A similar association was also
found after adjusting for LVEDD and further adjusting for other
variables in Table 1. The interactions between NT-proBNP and
age, gender, BMI, prevention indication, ICM/DCM, NYHA
functional class, AF, creatinine, and LVEF were not statistically
significant (all p > 0.1).
The restricted cubic spline shown in Figure 4 displays the
association between NT-proBNP and all-cause mortality (p for
nonlinearity < 0.001). The risk of all-cause mortality increased
rapidly until it reached the inflection point, which was equal to
3,231.4 pg/ml. Above this point, the curve was relatively flat,
which meant that the risk would not increase afterward.
DISCUSSION
The prognostic importance of NT-proBNP has been broadly
studied in patients with HF, but remains largely unexplored in
HF patients with ICD. In our study, we found that patients
with higher NT-proBNP levels had a lower survival probability,
however, did not have a higher risk of appropriate shock.
Therefore, these patients might derive less benefit from an ICD
implant. Our study validated the prognostic importance of NTproBNP associated with all-cause mortality in previous studies.
Nonetheless, our findings raised key questions about the utility
of NT-proBNP in the risk stratification of SCD.
Relationship Between NT-proBNP and First
Appropriate Shock
Cumulative incidence curves according to NT-proBNP quartiles
in Figure 3B did not show a difference in time to the first
appropriate shock (p = 0.885). In the multivariable competing
risk analyses shown in Table 2, NT-proBNP, regardless of
whether it was coded as a categorical variable or log-transformed
as a continuous variable, did not show a significant association
with the first appropriate shock after adjusting for variables
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urgent need to find a new risk stratification marker in addition
to LVEF and NYHA. Since published data have shown that NTproBNP has a close relationship with all-cause mortality (15, 16),
pump failure death (15, 16), and sudden death in a variety of
populations (21–27), it is also expected to be a promising marker
for HF with ICD.
As expected, we demonstrated that NT-proBNP conferred
an increased risk of all-cause mortality. Nonetheless, particular
attention must be paid that our population was comprised
of patients with ICD, in which death due to cardiac arrest
was greatly prevented (6, 7). Therefore, it could be speculated
that the predominant modes of death were pump failure in
our setting. In this regard, our finding was consistent with
previous studies showing that higher NT-proBNP was associated
with an increased risk of HF death (24, 25, 27, 30). To the
best of our knowledge, our study is the first to characterize
NT-proBNP levels with all-cause mortality using a smooth
spline in patients with ICD patients. The spline illustrated the
relationship between NT-proBNP and all-cause mortality as a
logarithmic curve. This was also in line with our finding that
log-transformed NT-proBNP was a significant predictor in the
multivariable models. Therefore, it justifies the convention that
NT-proBNP should be log-transformed in the data analysis
process (18, 22, 24, 27). Furthermore, our results showed that
once the NT-proBNP level surpassed the inflection point, the
risk of all-cause mortality would not increase further. This
might reflect the ceiling effect of NT-proBNP. Unfortunately,
most previous studies failed to find this effect (24, 25, 27,
30). Of note, our inflection point might not be suitable for
other populations. Nonetheless, it shows a phenomenon that an
extremely high NT-proBNP value does not necessarily translate
into an extremely high risk of death. This might be explained by
the fact that even when the NT-proBNP level is high, it could be
considerably reduced when treatments are further intensified in
stable patients (15, 31–33). However, we cannot rule out that this
finding represented the play of chance. It needs to be replicated
in the future.
In contrast with published studies, we failed to demonstrate
the connection between NT-proBNP and SCD, which was
substituted by appropriate shock in our study. In fact, according
to the definition of SCD (34), precise adjudication of SCD was
almost impossible except for evidence found at autopsy. In this
regard, the endpoint we used might be more accurate to reflect
the actual rate of sudden death from a cardiac cause. On the
other hand, since NT-proBNP is a surrogate for intracardiac
volumes and filling pressures (15, 20, 35), echocardiographic
parameters might reflect this nature more directly. Among these,
LVEDD was proved to have a positive relationship with increased
intracardiac pressures and also to be positively correlated with
NT-proBNP (36). A case-cohort study of 418 patients with SCD
and 329 controls based on the general population suggested that
moderate or severe left ventricular dilation was an independent
predictor of SCD (37). Given the strong relationship between NTproBNP and LVEDD, inference can only be considered robust
when two variables are put together in the multivariable model.
Otherwise, it might lead to a biased result. However, most
studies failed to adjust for LVEDD in their analyses (22, 23, 26,
FIGURE 3 | Survival curves for all-cause mortality (A) and cumulative
incidence curves for first appropriate shock (B) according to NT-proBNP
quartiles (Q1–Q4). NT-proBNP quartiles were defined as Q1, NT-proBNP ≤
401.9 pg/ml; Q2, NT-proBNP 402.0 ≤ 854.2 pg/ml; Q3, NT-proBNP 854.3 ≤
1,817.7 pg/ml; Q4, NT-proBNP ≥ 1,817.8 pg/ml.
According to current guidelines (6, 7), a lot of HF patients
implanted with ICDs would not receive appropriate ICD shock
in the long-term follow-up (8–11). Consequently, there is an
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TABLE 2 | Unadjusted and adjusted hazard ratios (HRs) and subdistribution HRs of outcomes.
Outcome
Events,
no.
Incidence rate,
per 100
person-years
Model 1
unadjusted
HR/sdHR#
(95% CI)
Model 3†
Model 2*
P value
adjusted
HR/sdHR#
(95% CI)
P value
adjusted
HR/sdHR#
(95% CI)
Model 4
‡
P value
fully adjusted
HR/sdHR#
(95% CI)
0.221
1.60 (0.64, 3.99)
0.313
4.17 (1.80, 9.63) <0.001 3.99 (1.74, 9.12)
0.001
P value
All-cause mortality
NT-proBNP quartile
1
7
1.48
2
14
2.66
1 [Reference]
1 [Reference]
3
32
6.76
4.52 (1.99,
10.25)
<0.001 3.98 (1.71, 9.25) 0.001
4
53
12.66
8.37 (3.80,
18.42)
<0.001
1.79 (0.72, 4.43) 0.211
1 [Reference]
1.77 (0.71, 4.43) 0.223
5.90 (2.43,
14.30)
<0.001
1 [Reference]
1.77 (0.71, 4.42)
6.33 (2.64,
15.14)
<0.001
6.61 (2.92,
14.98)
<0.001
P for trend§
<0.001
<0.001
<0.001
<0.001
P for nonlinearity
<0.001
<0.001
<0.001
<0.0001
log10(NT-proBNP)
5.46 (3.46, 8.61) <0.001 4.16 (2.32, 7.48) <0.001 4.40 (2.47, 7.82) <0.001 5.10 (3.03, 8.57)
<0.001
First appropriate shock
NT-proBNP quartile
1
17
7.80
2
22
8.01
1.10 (0.58–2.07) 0.769
1.03 (0.54–1.97) 0.938
1.02 (0.53–1.95)
0.952
1.12 (0.59–2.12)
0.738
3
25
9.33
1.23 (0.66–2.29) 0.507
1.10 (0.56–2.14) 0.783
1.14 (0.59–2.19)
0.696
1.28 (0.68–2.43)
0.452
4
25
11.46
1.27 (0.68–2.35) 0.449
1.13 (0.53–2.37) 0.757
1.18 (0.57–2.42)
0.661
1.27 (0.65–2.47)
0.404
0.729
P for trend§
P for nonlinearity
log10(NT-proBNP)
1 [Reference]
1 [Reference]
1 [Reference]
0.751
0.666
1.25 (0.80–1.95) 0.334
1.12 (0.64–1.96) 0.688
1 [Reference]
0.604
0.774
1.15 (0.67–1.99)
0.608
0.483
0.434
0.771
1.21 (0.74–1.98)
0.443
* Model
2 was adjusted for age, smoking, prevention indication, ICD/DCM, NYHA class, BMI, diabetes, AF, hemoglobin, creatinine, LVEF, and use of diuretics and digoxin.
Model 3 was adjusted for age, smoking, prevention indication, ICD/DCM, NYHA class, BMI, diabetes, AF, hemoglobin, creatinine, LVEDD, and use of diuretics and digoxin.
‡ Model 4 was fully adjusted, such as all variables in model 3 and sex, device type, NSVT, PVC, hypertension, BUN, LVEF, use of ACEI/ARB, sacubitril/valsartan, Beta-blockers, MRA,
and use of amiodarone and statin. Stepwise regression by AIC rule with the forced entry of NT-proBNP was used.
§P for linear trend was calculated by including each corresponding quartile as a continuous numeric variable.
#The HR and subdistribution HRs were used for the Cox and Fine-Gray models, respectively.
sdHR, subdistribution hazard ratio; other abbreviations as in Table 1.
†
(20). The authors found that NT-proBNP was not associated
with its combined outcomes including death from any cause
while it was positively associated with appropriate ICD therapies.
An earlier study also revealed that NT-proBNP was associated
with both appropriate ICD therapies and total mortality (19).
In contrast, our finding was consistent with the risk prediction
model developed by Bergau et al. (41), in which NT-proBNP was
a predictor of all-cause mortality, while it was not a predictor
of ICD shock (42). Disparities between these studies might be
explained by their population, conduction, and slightly different
definitions of endpoints. Most importantly, these studies failed
to handle the Non-normality of NT-proBNP properly, where the
first two simply dichotomized it while the third treated it as
a continuous normal distribution variable. In this regard, their
conclusions were less reliable than ours.
Our study has some limitations. First, the mean follow-up
duration of shock status was less than that of survival status.
It might undermine the power of our analysis. However, it is
comparable with other studies (19, 23) dedicated to solving this
hypothesis. Moreover, the follow-up period does not have an
influence on the HR in the proportional hazards model in the
27, 38). Furthermore, although NT-proBNP showed significant
associations with SCD (22, 38), a cause-and-effect relationship
might not exist. A variety of studies have demonstrated that
NT-proBNP has a stronger relationship with all-cause mortality
and pump failure death than SCD (23–25, 27) by showing a
higher HR. Clinical models, including NT-proBNP, to predict
pump failure death also showed better discrimination ability
than to predict SCD (24, 38). These findings indicate that NTproBNP might not have a direct effect on SCD. Conversely, it
might be just a marker of HF progression (39). As a result,
the Danish study to assess the efficacy of ICDs in patients with
non-ischemic systolic heart failure on mortality (DANISH) trial
found that only patients in the subgroup of NT-proBNP <1,177
pg/ml had an increased benefit of ICD implant (10). Instead, we
found that LVEDD was a predictor of SCD, consistent with a
previous meta-analysis that included four relevant studies (40).
This finding further indicates that NT-proBNP might not be a
proper predictor for SCD. In conclusion, a single NT-proBNP
level should not be used as a risk stratification tool for SCD.
Our finding was contrary to an analysis of 342 patients with
primary prevention ICD after a median follow-up of 35 months
Frontiers in Cardiovascular Medicine | www.frontiersin.org
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March 2022 | Volume 9 | Article 823076
Deng et al.
NT-proBNP in Implantable Cardioverter-Defibrillator
did not include anti-tachycardic pacing, which might also be
triggered by fatal arrhythmic events. In fact, the inclusion of antitachycardic pacing is not proper because it was mainly designed
for treating hemodynamically stable, slower rate ventricular
tachyarrhythmia. As a result, only appropriate shock was
included as the endpoint.
CONCLUSION
We conducted a thorough exploration of the association of NTproBNP with all-cause mortality as well as the first appropriate
shock by restricted cubic spline analysis. We found increasing
NT-proBNP levels were related to an increased risk of death
with a ceiling effect at 3,231.4 pg/ml, but not related to the first
appropriate shock. Therefore, patients with higher NT-proBNP
might derive less benefit from ICD implant. It still needs further
investigation to confirm our results.
FIGURE 4 | Distributions of NT-proBNP in the overall population and adjusted
hazard ratios (HRs) of all-cause mortality according to NT-proBNP levels. This
plot demonstrates the nonlinear relationship between baseline NT-proBNP
levels and the risk of all-cause mortality. A single inflection point was found at
3,231.4 pg/ml. Increases in NT-proBNP from 0 to 3,231.4 pg/ml were
associated with a rapid increase in mortality risk but further increases in
NT-proBNP >3,231.4 pg/mL were not associated with an increased risk (p for
nonlinearity < 0.001). The dotted line indicates the corresponding 95% CIs.
The 25th percentile of NT-proBNP (402.0 pg/ml) was set as a reference. A
density plot is also drawn to show the distribution of NT-proBNP.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included
in the article/supplementary material, further inquiries can be
directed to the corresponding author.
ETHICS STATEMENT
The studies involving human participants were reviewed
and approved by Ethics Committee of Fuwai Hospital. The
patients/participants provided their written informed consent to
participate in this study.
absence of time-varying variables (43). Second, we only explored
the baseline effect of NT-proBNP instead of repetitive levels.
Dynamic changes in NT-proBNP levels and echocardiography
parameters might provide incremental information on prognosis
(30–33, 44). For example, an improvement in LVEF was
associated with reduced ICD therapy and lower mortality (44).
However, due to the retrospective nature of our study, it is
hard to strictly choose unified timepoints to define serial change.
Nonetheless, our study demonstrated that a single baseline
NT-proBNP level was a predictor of death, which is easier
to interpret and use in clinical setting. Third, our endpoint
AUTHOR CONTRIBUTIONS
WH, YD, SZ, H-XN, X-HC, MG, and CC contributed to
conception and design of the study. YD, N-XZ, XL, M-SC, S-JC,
and HH organized the database. YD and M-SC performed the
statistical analysis. YD wrote the first draft of the manuscript. WH
revised the manuscript. All authors contributed to manuscript
revision, read, and approved the submitted version.
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